1. Field of the Invention
This invention relates generally to a system and method for detecting the position of a vehicle in a roadway lane and centering the vehicle in the lane and, more particularly, to a system and method for detecting the position of a vehicle in a roadway lane and centering the vehicle in the lane by identifying lane markers from a video sequence of the lane and providing steering control for lane centering.
2. Discussion of the Related Art
The operation of modern vehicles is becoming more autonomous, i.e., vehicles are able to provide driving control with less driver intervention. Cruise control systems have been on vehicles for a number of years where the vehicle operator can set a particular speed of the vehicle, and the vehicle will maintain that speed without the driver operating the throttle. Adaptive cruise control systems have been recently developed in the art where not only does the system maintain the set speed, but also will automatically slow the vehicle down in the event that a slower moving vehicle is detected in front of the subject vehicle using various sensors, such as radar, lidar and cameras. Modern vehicle control systems may also include autonomous parking where the vehicle will automatically provide the steering control for parking the vehicle, and where the control system will intervene if the driver makes harsh steering changes that may affect vehicle stability and lane centering capabilities, where the vehicle system attempts to maintain the vehicle near the center of the lane. Fully autonomous vehicles have been demonstrated that drive in simulated urban traffic up to 30 mph, while observing all of the rules of the road.
As vehicle systems improve, they will become more autonomous with the goal being a completely autonomously driven vehicle. Future vehicles will likely employ autonomous systems for lane changing, passing, turns away from traffic, turns into traffic, etc. As these systems become more prevalent in vehicle technology, it will also be necessary to determine what the driver's role will be in combination with these systems for controlling vehicle speed, steering and overriding the autonomous system.
Examples of semi-autonomous vehicle control systems include U.S. patent application Ser. No. 12/399,317 (herein referred to as '317), filed Mar. 6, 2009, titled “Model Based Predictive Control for Automated Lane centering/changing control systems,” assigned to the assignee of this application and herein incorporated by reference, which discloses a system and method for providing steering angle control for lane centering and lane changing purposes in an autonomous or semi-autonomous vehicle. U.S. patent application Ser. No. 12/336,819, filed Dec. 17, 2008, titled “Detection of Driver Intervention During a Torque Overlay Operation in an Electric Power Steering System,” assigned to the assignee of this application and herein incorporated by reference, discloses a system and method for controlling vehicle steering by detecting a driver intervention in a torque overly operation.
Modern lane centering/keeping systems typically use vision systems to sense a lane and drive the vehicle in the center of the lane. One method that enables the use of vision systems requires calibrating the camera and correlating the length/distance on the images from the camera with the corresponding length/distance in the real world. To know the relationship between the image and the real world coordinates requires calibration of the vision system to the real world. The calibration is necessary because of a number of distortions including those caused by the camera lens, variations in the mounting position and variations in the mounting direction of the camera. With a calibrated camera, information about the length/distance in the image is translated into a length/distance in the real world and that information is given to an autonomous steering module to calculate steering commands to steer the vehicle to the center of the lane. However, this calibration and translation between image size and real world length/distance is labor and computationally intensive.
A need exists for a lane centering system and method that does not require camera calibration and translation and can still allow accurate centering of the vehicle in the lane.